Proceeding report of the third symposium on Hidradenitis Suppurativa advances (<scp>SHSA</scp>) 2018
Bibliographic record
Abstract
Abstract The 3rd Annual Symposium on Hidradenitis Suppurativa Advances (SHSA) took place on 12‐14 October 2018 at the Women's College Hospital in Toronto, Ontario, Canada. This symposium was a joint meeting of the Hidradenitis Suppurativa Foundation (HSF) founded in the USA and the Canadian Hidradenitis Suppurativa Foundation (CHSF). This cross‐disciplinary meeting with experts from around the world was an opportunity to discuss the most recent advances in the study of hidradenitis suppurativa pathogenesis, epidemiology, classification, scoring systems, radiologic diagnosis, treatment approaches and psychologic assessment. Two special sessions this year were HS as a systemic disease and HS management guidelines. There were focused workshops on wound healing and ultrasound. There were two sessions primarily for patients and their families in the HS School programme: One workshop focused on mindfulness, and the second involved discussion among clinicians and patients about various disease aspects and the latest management. To facilitate networking between clinical and research experts and those early in their career, a mentoring breakfast was held.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.063 | 0.015 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".